Figure REF  is the tSNE [1]} visualisation of the features learnt by SCR and our SDAF, both models complete the training of the 5th stages on CIFAR-10 dataset with \(\mathcal {M}\)  being set to 500. This visualisation result shows the effectiveness of our SDAF method in separating trained classes (i.e. inlier, from the test split of CIFAR-10 dataset) from unseen classes (i.e. outlier, from the test split of SVHN dataset), which actually implies that our SDAF method is better generalised to unseen classes hence will suffer less from the forgetting issue while learning to recognize the new classes.
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